2026 PhD Graduate - Postdoctoral Researcher - In-Situ Sensing for Additive Manufacturing

Overview Are you passionate about pioneering advancements in additive manufacturing through cutting-edge sensing technologies, data fusion, and real-time control? Do you want to contribute to critical national challenges by enabling intelligent closed-loop monitoring and control of metal additive manufacturing processes? Join our innovative research team in the Research and Exploratory Development Department (REDD) at the Johns Hopkins University Applied Physics Laboratory (JHU/APL). As an In-Situ Sensing Postdoctoral Fellow, you will develop and integrate novel sensing modalities, artificial intelligence (AI), and machine learning (ML) algorithms to enhance process control, optimize material properties, and ensure the reliability of additively manufactured components. Your work will be essential in designing closed-loop control systems that adapt dynamically to real-time process data, enabling unprecedented advancements in manufacturing precision and efficiency. Our team is actively developing next-generation sensing and control solutions that will allow real-time adjustments to critical additive manufacturing parameters, such as laser power, scan speed, and material feed rate. By leveraging multi-modal sensor data—including optical, thermal, acoustic, and X-ray imaging—you will help to create intelligent feedback systems capable of identifying defects, predicting failure points, and optimizing manufacturing conditions. These advances will not only push the limits of metal additive manufacturing but will also enable new applications in mission-critical environments where reliability is paramount. As an In-Situ Sensing Postdoctoral Fellow, you will… Responsibilities Collaborate with APL scientists, engineers, and technicians to develop novel closed-loop sensing and control solutions tailored for additive manufacturing. Perform pioneering research in materials and process characterization by fusing in-situ sensing modalities to optimize microstructure and density in metal additive manufacturing. Utilize AI and ML algorithms to extract insights from multi-modal sensor data, improve real-time process monitoring, and drive automated control systems. Design, implement, and validate adaptive control algorithms that leverage sensor feedback to dynamically adjust processing parameters in real time. Engage with a multidisciplinary team focused on materials discovery, novel fabrication techniques, multiscale modeling, processing insights, advanced testing, and qualification science. Present technical findings to both internal and external audiences, effectively communicating complex concepts to team members, task leads, and project leadership. Contribute to the design, fabrication, and characterization of additively manufactured operational prototypes that demonstrate intelligent process control. Minimum Qualifications Ph.D. in Mechanical Engineering, Electrical Engineering, Materials Science, Data Science, or a related field. Strong written and oral communication skills, with the ability to engage broad audiences and adapt to different communication styles. Adaptable, enthusiastic about new challenges, and collaborative with a mindset open to feedback. Experience solving multidisciplinary research challenges related to qualified hardware and additive manufacturing. Fundamental understanding of additive manufacturing, including process defects, microstructure evolution, and thermodynamic solidification. Demonstrated track record of authoring research proposals and publishing high-impact journal papers. Willing and able to work in a laboratory setting and travel for field testing, sponsor meetings, conferences, and technical presentations. Ability to obtain a Secret-level security clearance to start with APL; final Top Secret clearance may be required. If selected, you will be subject to a government security clearance investigation and must meet eligibility requirements for access to classified information, including U.S. citizenship. Preferred Qualifications Experience fielding additively manufactured components. Ability to fuse 2D and 3D data, including in-situ and post-manufacturing data, into a 3D format for advanced processing and visualization. Experience applying AI/ML techniques to complex datasets, including deep learning models for defect detection, anomaly detection, and predictive modeling of additive manufacturing processes. Hands-on expertise in developing novel in-situ monitoring methods for additive manufacturing, including custom sensor development to improve signal-to-noise ratios and spatial registration. Experience with digital twin technology and reinforcement learning for real-time optimization of manufacturing parameters. Experience working with voxel-based data and mapping physical quantifications across multiple sensing platforms. Strong scientific programming skills using MATLAB or Python, with experience in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn. We are seeking a postdoctoral fellow with proven expertise in in-situ sensing, AI, and data fusion for additive (or other advanced) manufacturing processes to drive innovation in real-time monitoring and closed-loop control of advanced manufacturing systems. In this role, you will collaborate with a multi-disciplinary team to demonstrate multi-modal (e.g., optical, thermal, acoustic) in-situ sensing and real-time adaptive control in advanced manufacturing environments. At APL, we encourage our team members to generate and lead their own research initiatives while also publishing their findings in high-impact venues. We are a collaborative, risk-taking, and innovative research team dedicated to solving complex technical challenges with national impact. If you are excited about the opportunity to shape the future of additive manufacturing through sensing, AI, and adaptive control systems, we would love to hear from you! Compensation The Johns Hopkins University Applied Physics Laboratory (APL) offers a comprehensive benefits package and compensation. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact View email address on click.appcast.io. The referenced pay range and compensation details are provided for informational purposes. Actual compensation may vary based on geographic location, work experience, market conditions, education, and skill level. Applications are accepted on a rolling basis. Minimum Rate $85,300 Annually Maximum Rate $155,500 Annually #J-18808-Ljbffr Johns Hopkins Applied Physics Lab